Microsoft Healthcare Germany

Boehringer Ingelheim

Enterprise Knowledge Search

The challenge: The sheer number of documents makes it hard to find the right information

Reported impact

Business outcome

Boehringer Ingelheim is also benefiting from the high compatibility of Microsoft solutions. iQNow is integrated directly into Word PowerPoint —the two programs in which the lion’s share of drug development documents are written. “We’ve named this plug-in iQMe,” Kapisoda says.

  • Productivity Improvement

Solution

The challenge: The sheer number of documents makes it hard to find the right information How can expert knowledge be used efficiently? Typically, someone comes up with a question and searches until they’ve found their answer. In the pharmaceutical industry, coming up with the answer quickly can save many lives. There’s no time to lose when it comes to developing medications—it’s imperative that lifesaving drugs are made available to those who need them as quickly as possible. This is why time is the key metric in many process steps: development, clinical trials, and approval by the responsible authorities. As pharmaceutical companies must observe a clear set of rules and requirements, they have only a limited influence on the efficiency of many process steps.

Data flow

Content from SharePoint is ingested into Azure OpenAI Service, where it is indexed, enriched, or reasoned over before grounded answers are returned to employees through business applications.

Solution architecture

2 components · 2 layers
  1. Compute
    • Azure OpenAI Service Provides large language model inference for natural language search, drafting, summarization, and recommendations.
  2. Storage
    • SharePoint Hosts source documents and collaboration content that downstream apps automate or analyze.

Architecture clues

  • Azure OpenAI Service: Provides large language model inference for natural language search, drafting, summarization, and recommendations.
  • Integrates with SharePoint.
  • SharePoint: Hosts source documents and collaboration content that downstream apps automate or analyze.

Evidence from the source

Boehringer Ingelheim is also benefiting from the high compatibility of Microsoft solutions. iQNow is integrated directly into Word PowerPoint —the two programs in which the lion’s share of drug development documents are written. “We’ve named this plug-in iQMe,” Kapisoda says.
How can expert knowledge be used efficiently? Typically, someone comes up with a question and searches until they’ve found their answer.
The challenge: The sheer number of documents makes it hard to find the right information
There’s no time to lose when it comes to developing medications—it’s imperative that lifesaving drugs are made available to those who need them as quickly as possible. This is why time is the key metric in many process steps: development, clinical trials, and approval by the responsible authorities.
“Over the lifecycle of any one of our products, a single department will produce more than 60,000 documents of every conceivable format—and that can involve anywhere up to 5,000 experts. These documents contain knowledge that is extremely valuable to other projects as well,” says Michael Schorpp, Senior Expert Knowledge and Learning Architecture & Strategy at Boehringer Ingelheim .
Transparency Evidence & methodology 58/100 reference value · 87% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value58/100
  • Problem clarity12/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Microsoft

    Boehringer Ingelheim customer story

    First-party
    https://www.microsoft.com/en/customers/story/1693653851333576209-boerhingeringelheim-azureopenaiservices-en
    Source type
    Vendor-published customer story
    Published
    Oct 24, 2023
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page Oct 24, 2023 · Microsoft · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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